We would like to thank David Pitcher for his valuable contribution to this TMS experiment. This research was funded&#160;by a fellowship from the Levie-Edersheim-Gitter Institute for Brain Mapping&#160;to B.S, a grant from the Wolfson Foundation; grants 65/08 and 1657/08 from the Israeli Science Foundation&#160;and a travel grant from the British Council Researcher Exchange&#160;Programme to G.Y.&#160;The experiment was conducted at the Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Center.

The experiment is conducted in two separate sessions. During the first session a functional MRI experiment (e.g. a functional localizer) is carried out in order to define the desired TMS target areas on an individual subject basis. The fMRI results are then fed into a stereotactic navigation system for an accurate TMS targeting. The second session is held following the analysis of the fMRI data, during which EEG is recorded concurrently with TMS. The protocol described here was approved by the ethics committee of the Tel-Aviv Sourasky Medical Center.
In the example given in this paper, data were analyzed with MATLAB&#160;version 7.7 (R2008b).&#160; The Statistical Parametric Mapping (SPM 5) software for MATLAB&#160;and MarsBar toolbox for SPM 23 were used for fMRI data processing.
1. fMRI Session and fMRI Data Analysis
<ol>
	<li>Run a functional MRI task using an echo planar imaging (EPI) sequence to determine the desired foci of activation to be targeted with TMS. For a better dissociation between adjacent areas, such as the OFA and EBA in the example below, high-resolution scanning is recommended. Voxels of 3 mm3 or smaller, obtained with an MRI head-coil of 8 channels or more, are sufficient for delineating adjacent regions.</li>
	<li>Run a T1-weighted structural scan to obtain neuroanatomical data. Make sure that the face of the participant is entirely included in the field of view of this scan, since external markers on the image (e.g. the tip of the nose) will be later used to coregister the subject&#39;s head with its scan.</li>
	<li>After data collection, use the MarsBar toolbox for SPM to define the desired brain regions of interest based on contrasts between the experimental conditions. Use the contrasts face&#62;objects to define the Occipital Face Area (OFA), and bodies&#62;objects to define the Extrastirate Body Area (EBA). To further ensure that the two cortical targets are functionally distinct, use &#34;conjunction&#34; (in MarsBar) to mask from each ROI any voxels responding to the other experimental condition (exclude face-voxels from the EBA, and body-voxels from the OFA).</li>
	<li>Corregister the structural T1 images with the functional scans, using SPM.</li>
	<li>Copy the files of the structural scan, as well as the relevant functional contrast files, to a portable drive in order to upload to the navigation system.</li>
</ol>
2. Preparing a Paradigm for the EEG-TMS Experiment that will allow ERP Extraction
Described in the section below is a method for collecting EEG data during TMS application in a way that allows extraction of reliable and replicable ERPs19. The advantage of this technique is that it easily handles the secondary, long lasting, TMS artifact, and is robust enough even to allow restoration of data at electrodes located right under the TMS coil, where the artifact is of the highest voltage and longest duration.
<ol>
	<li>Organization of the paradigm
	<ol>
		<li>Run the different TMS conditions (the different target brain areas, as well as a no-TMS condition) in separate blocks.</li>
		<li>Within each block present the participant with all stimulus conditions (e.g. faces, objects, scenes and so forth) randomly in an event-related design.</li>
		<li>For better quality of ERP and TMS-noise template (below) make sure to have at least 50 trials per condition.</li>
	</ol>
	</li>
	<li>Set the timing of the TMS pulse/pulses to the desired latency after image onset. This is done via writing to a parallel port, from which a cable goes to the TMS stimulator. This function is available in most software for psychological experiments, such as Psychtoolbox (versions 2 or 3) for MATLAB&#160;24 or E-Prime (see Materials Table). Jitter the inter stimulus interval (ISI) to reduce stimulus (and pulse) predictability (e.g. add a random value between 0 to 500 msec at each ISI).</li>
	<li>Prepare an additional blank-screen condition:
	<ol>
		<li>Prepare trials during which TMS will be applied at the same intensity, but with no stimulus presentation on the screen. These blank-screen TMS trials will be served to calculate a TMS artifact template in the absence of visual stimulation.</li>
		<li>Set the number of repetitions of the blank trials to be identical to the number of repetitions of any one of the experimental conditions within the block.</li>
		<li>For an accurate representation of the shape of the TMS residual artifact, randomize the blank trials throughout the whole block rather than presenting them all at the beginning or at the end.</li>
	</ol>
	</li>
</ol>
3. Setting up the EEG and the Neuronavigation System, and Conducting the Experiment
Accurate TMS targeting of individually defined ROIs is possible with the use of a stereotactic navigation system, comprised of an infrared camera, infrared sensors mounted on the participant&#39;s head, and a specialized software.
<ol>
	<li>Screen participants based on TMS safety criteria. Exclude from participation subjects with a self or family history of epilepsy, subjects with other neurological conditions or with frequent migraines, and subjects on psychoactive drugs. Although not typically screened for, subjects with suspicion for autonomic disorders such as vasovagal syncopes (mostly manifested as a tendency to faint easily) may also be excluded. Instruct participants to avoid alcoholic drinks starting the prior evening, and caffeinated drinks at least 2 hr&#160;before the experiment.&#160; For further instructions and discussion of safety see Rossi&#160;et al25, and the Magstim safety review (<a href="http://joedevlin.psychol.ucl.ac.uk/tms/docs/magstim_safety.pdf">http://joedevlin.psychol.ucl.ac.uk/tms/docs/magstim_safety.pdf</a>).</li>
	<li>Prepare the neuronavigation system:
	<ol>
		<li>Before the session starts, feed the structural scan files into the navigation system&#39;s software.</li>
		<li>Overlay the functional MRI results (the contrasts) on the structural images.</li>
		<li>Using the Neuronavigation software, mark the desired targets on the images, as well as the external anatomical markers that will serve for coregistration: the tip of the nose, the deepest part of the nose bridge often referred to as nasion, and the tragus of each ear.</li>
	</ol>
	</li>
	<li>Mount the EEG cap on the participant&#39;s head and connect the electrodes:
	<ol>
		<li>Try to keep electrode impedance not higher than 5 k&#937;.</li>
		<li>To avoid TMS-related heating of the electrodes, use as little gel as possible. To achieve good impedance with little amount of gel perform a thorough skin preparation. Optionally, ask participants to wash their hair before coming to the experiment.</li>
		<li>Make sure that the electrode wires do not cross each other and are oriented away from the coil&#39;s location. Avoid loops in the wires.</li>
		<li>Use a high sampling rate for a better representation of the noise artifact. It is recommended to use 1 kHz or above, as most previous studies using this method have done7,26-28.</li>
		<li>Place the reference and ground electrodes as far from the coil as possible. In this example, areas in the occipital cortex were targeted using a nose reference and an Fz ground7. For other examples see3,4,27,29,30. Note that data can be re-referenced offline to a new reference as needed, such as the common average. 
		Note: For a review about optimization of TMS-EEG setup, see Veniero et al31.</li>
	</ol>
	</li>
	<li>Coregister the subject&#39;s head with the scan, as follows:
	<ol>
		<li>Mount the infrared detectors on the participant&#39;s head.</li>
		<li>Coregister the head location with the navigation system using the predefined markers (tip of the nose, etc. See Figure&#160;3). It is advised to repeat the coregistration between blocks to ensure accurate coil placement at all stages.</li>
	</ol>
	</li>
	<li>Locate the target areas:
	<ol>
		<li>Have the subject seated with the chin resting on a chinrest at the desired distance from the screen.</li>
		<li>Make sure the participants are comfortable at their chair, as they are asked to refrain from movements during the experimental blocks (important for an accurate noise-template measurement).</li>
		<li>Choose a TMS target from the navigation system Figure&#160;3.</li>
		<li>Using the pointer tool (see Materials Table), let the navigation system guide the user to the optimal coil location and mark it with a small sticker on the electrode cap. It is important to hold the pointer perpendicular to the head. Repeat this stage prior to each block. Note that it is not recommended to use online navigation during the block (navigating the coil itself while holding it) since any coil movement should be avoided for a best measurement of the TMS artifact template. It was found that predefining and marking the TMS location is the optimal way to achieve stable stimulation.</li>
		<li>Guide the coil&#39;s precise center to the marker, while being held by a holder. Make sure it is tangential to the head.</li>
	</ol>
	</li>
	<li>Set the TMS intensity to the desired value. Administer one test pulse for the participant&#39;s approval.</li>
	<li>Run the experimental block.</li>
	<li>No-TMS condition: if a specialized sham TMS coil is not available, place the TMS coil next to the subject&#39;s head and tilt it in 90&#176;. Run the block as usual, including the blank trials. 
	The reader may also refer to the JoVE video paper by Andon and Zatorre32 for further demonstration of the navigation system.</li>
</ol>
4. Analyzing the EEG Data and Computing ERP
<ol>
	<li>Remove the immediate pulse artifact, as follows:
	<ol>
		<li>If a clipping device is not available (see above), the first step in the EEG data processing would be to cut out the immediate TMS pulse artifact itself from the data. Note that this step can be skipped if filters are not desired. But if filters are applied, the sharp-edge shape of the artifact will create distortions in the data. A narrow time-window of 10 to 15 msec after pulse onset should suffice, but be sure to verify this by visual inspection of the data.</li>
		<li>Connect the two cut ends created after pulse removal. Two main methods for accomplishing this have been suggested in previous reports: 1. simply join together the two ends remaining after pulse removal (see Fuggetta&#160;et al.26 and Figure&#160;1); 2. interpolate a line between the two cut ends by generating equally spaced values between them7. The equation used for this interpolation is as follows: for each missing data point y at sample x, compute y=y0+((y1-y0)*(x-x0))/(x1-x0) where x0 and y0 are the coordinates for the last data point before the cut segment, and x1 and y1 are the coordinates for the first data point after the cut segment. Both techniques assure that filters can be applied on the data without producing ripples due to sharp voltage steps, as demonstrated in Figure&#160;1. Refer to the work by Reichenbach and colleagues27 for a more complex 3rd order polynomial interpolation.</li>
	</ol>
	</li>
	<li>Apply the subtraction method:
	<ol>
		<li>For each experimental block, including a no-TMS control condition if present, calculate an averaged ERP to the blank screen trials by time-locking them to trial start (as if an image had been presented).</li>
		<li>Subtract this averaged template from each trial of all other stimulus conditions. If several blocks were run for the same stimulation site, do this separately for each block, as the template will be slightly different between the blocks.</li>
	</ol>
	</li>
	<li>All other preprocessing and processing steps are carried out as in any other ERP experiment.</li>
</ol>

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The authors declare that they have no competing financial interests.

Having the unique ability to momentarily disrupt normal neuronal activity in selected cortical areas, in precise time points and with a relatively good spatial accuracy, TMS allows to causally link a stimulated brain area with a behavioral or a neurophysiological measure. In this paper we described a method for measuring EEG during concurrent TMS application, targeting functionally defined cortical areas, and applying an analysis that enables a reliable measuring of ERP responses. We gave an example from the literature i...

Transcranial Magnetic Stimulation (TMS) generates momentary interference to the normal neural activity in target areas of the brain. By creating this transitory neural interference and measuring a behavioral or physiological change, we can draw a causal link between the target area and the measured experimental effect (for a review see Pascual-Leone et al. and Taylor et al.1,2). Such an experimental effect may be, for example, a performance on a cognitive task or a change in electrophysiological (EEG) activity. Indeed, in recent years researchers have started using TMS in combination with EEG to directly relate cortical areas with event-related potentials (ERP) or oscillatory activity patterns (e.g.2-7). In this methodological paper we will describe a particular and useful framework for combining TMS and EEG: fMRI-guided TMS during an ERP experiment. First, we will detail how to apply TMS to areas predefined by fMRI, while recording EEG data. We will then describe an experimental design that allows extraction of reliable ERP. The goal of such an experiment is to causally link brain areas revealed with functional MRI to ERP components of interest. Lastly, we will give a specific example of a study relating face and body selective ERPs with face and body selective areas that are revealed with fMRI.
What is the benefit of linking EEG signals with fMRI activations? EEG and fMRI are commonly used tools to measure cortical responses to visual input. For example, category-selectivity in the visual pathway was assessed for different visual object categories such as faces, body parts, and written words, both by means of ERP extracted from EEG data8,9, and functional MRI10-12. The signals measured by these two common research tools are, however, of fundamentally different nature. EEG carries information about neural electrical activity with great temporal precision, but very low spatial resolution and may reflect a mixture of many separate underlying sources. The fMRI provides an indirect measure of neuronal activity relying on the slow hemodynamic changes occurring during stimulus presentation or/and task execution, but presents this activity with a higher spatial resolution. Establishing a correlation between the two measures can thus be of great interest, but is limited in that it does not imply a causal link between the scalp-recorded electrophysiological response and the areas revealed with functional MRI. Even when measured simultaneously (e.g.13-15), a directional causal relation between EEG and activity in functionally defined cortical areas cannot be determined. TMS is a tool that can assist achieving the establishment of such a causal relationship.
A simultaneous EEG-TMS study is methodologically challenging, mostly due to the high voltage artifact introduced to the EEG signal by the magnetic stimulation (see Figure 1, for a review see Ilmoniemi et al.16). This artifact consists of a transient short living pulse-related disturbance, often followed by a slower secondary (or residual) artifact that may last a few hundreds of milliseconds after the pulse is delivered Figure 2A, thus overriding most ERP components of interest. This secondary artifact may include mechanical sources such as currents induced by the magnetic pulse into the wiring and the slow decay of these currents in the skin, and physiological sources such as muscular activity over the scalp and auditory or somatosensory evoked potentials elicited by the operation of the coil17-20. Although the mechanical sources of interference probably produce larger amplitude artifacts than the physiological ones, these different artifacts cannot be separated, and the existence of any of them in the signal can confound the results. One possible solution is the application of repetitive TMS pulses prior to EEG recording (&#34;offline TMS&#34;), as opposed to simultaneous EEG-TMS. The inhibitory effect of such a protocol on cortical activity persists for several minutes (and up to half an hour) after the stimulation, and EEG can be measured during this effective time window and compared with baseline, pre-TMS, EEG data. Repetitive stimulation, however, is by definition lacking the high temporal resolution that online TMS may offer, where pulses can be administered at a precise timing relative to trial onset at the millisecond resolution. The effect of repetitive stimulation may also propagate via cortical connections across a wider area than desired and therefore significantly reduce the spatial resolution as well.
To take advantage of both the spatial and temporal resolution that TMS can provide, a simultaneous EEG-TMS combination can be applied. However, this requires methods for removal of artifacts generated by the magnetic stimulation on the EEG signal. Very few offline mathematical solutions for TMS artifact removal have been proposed16,21,22, although no method is agreed upon, and no one method may be optimal for all experimental designs. A &#34;clipping&#34; system, consisting of a sample-and-hold circuitry, was also developed to momentarily stop EEG acquisition during TMS pulse delivery 20. This technique not only requires specialized hardware, but may not completely remove the residual TMS artifact. In this paper we will describe an adaptation of an EEG-TMS methodology developed by Thut and colleagues19, particularly suitable for ERP studies. This technique allows reliable extraction of ERP while eliminating all the residual noise components caused by the TMS pulse Figure 2. We will further provide general guidance towards a successful EEG-TMS experimental setup.
Another challenge in TMS studies addressed in this methodological paper is finding the best coil position and angle for an accurate targeting of the desired cortical area. We will describe the use of a stereotactic navigation system to coregister the subject&#39;s head with the pre-acquired functional MRI images. Although the navigation system can be used to localize anatomically-defined brain structures, an fMRI-guided targeting is particularly useful since for many functions and experimental effects the precise location of activation cannot be inferred from anatomical markers alone. For such functional regions of interest (ROI), the definition of an area is made for each participant individually.
To illustrate all of the above, we will provide an example of a study we conducted previously, in which EEG was recorded concurrently with TMS guided by fMRI activations7. In this study, a double dissociation was made between face-selective and body-selective ERPs: although face and body ERPs peak around the same latency and electrode sites, targeting individually defined face-selective and body-selective areas in the lateral occipital lobe enabled us to dissociate the neural networks underlying each ERP response. Finally, we will try to give more general advise for optimizing EEG recording during TMS application.

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			<td height="43" style="height:43px;width:209px;">3.0T Signa MRI scanner</td>
			<td style="width:107px;">General Electric</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="63" rowspan="2" style="height:63px;width:209px;">BrainAmp&#160; amplifier&#160;</td>
			<td rowspan="2" style="width:107px;"><a name="RANGE!B3">Brain Products GmbH</a></td>
			<td rowspan="2" style="width:113px;">BP-01300</td>
			<td rowspan="2" style="width:167px;"></td>
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		<tr height="21">
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		<tr height="64">
			<td height="64" style="height:64px;width:209px;">Electrode input box</td>
			<td style="width:107px;">Brain Products GmbH</td>
			<td style="width:113px;"></td>
			<td style="width:167px;">Optional</td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:209px;">PowerPack - battery for amplifier</td>
			<td style="width:107px;">Brain Products GmbH</td>
			<td style="width:113px;">BP-02615</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="146">
			<td height="167" rowspan="2" style="height:167px;width:209px;">BrainCap - 32 flat electrodes on a flexible cap&#160;</td>
			<td rowspan="2" style="width:107px;">Brain Products GmbH</td>
			<td rowspan="2" style="width:113px;">BP-0300MR</td>
			<td rowspan="2" style="width:167px;">Flat electrodes should be used to assure a shorter distance beween coil and scalp. If larger (e.g. pin type) electrodes are used, remove the ones under the coil</td>
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			<td height="43" style="height:43px;width:209px;">TMS Super Rapid2 stimulator</td>
			<td style="width:107px;">Magstim</td>
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			<td height="22" style="height:22px;width:209px;">50mm double coil</td>
			<td style="width:107px;">Magstim</td>
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			<td height="169" style="height:169px;width:209px;">Coil holder&#160;</td>
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			<td style="width:167px;">Any mechanical arm or tripod that can hold the coil, be adjusted to the right angle and location, and keep the coil steady during stimulation</td>
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			<td height="22" style="height:22px;width:209px;">Chinrest</td>
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			<td height="43" style="height:43px;width:209px;">Polaris infrared camera</td>
			<td style="width:107px;">Rogue Research Inc</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
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		<tr height="43">
			<td height="43" style="height:43px;width:209px;">Polaris trackers and pointer tool</td>
			<td style="width:107px;">Rogue Research Inc</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
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		<tr height="43">
			<td height="43" style="height:43px;width:209px;">BrainSight workstation and software</td>
			<td style="width:107px;">Rogue Research Inc</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:209px;">BrainVision Recorder software</td>
			<td style="width:107px;">Brain Products GmbH</td>
			<td style="width:113px;">BP-00010</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:209px;">MATLAB software</td>
			<td style="width:107px;">The MathWorks Icn.</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="106">
			<td height="106" style="height:106px;width:209px;">SPM for Matlab</td>
			<td style="width:107px;">Wellcome Department of Imaging Neuroscience, London, UK&#160;</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:209px;">MarsBar region of interest toolbox for SPM</td>
			<td style="width:107px;"></td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="211">
			<td height="211" style="height:211px;width:209px;">Psychtoolbox for MATLAB</td>
			<td style="width:107px;"></td>
			<td style="width:113px;"></td>
			<td style="width:167px;">This toolbox and the E-prime software (below) are examples for stimulus presentation software capable of delivering commands to the TMS stimulator and to the EEG recorder with reliable timing</td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:209px;">E-Prime software</td>
			<td style="width:107px;">Psychology Software Tools, Inc.</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
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</table>

extracting visual evoked potentials from eeg data recorded during fmri-guided transcranial magnetic stimulation

Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological effects. Specifically, by creating a transient interference with the normal activity of a target region and measuring changes in an electrophysiological signal, we can establish a causal link between the stimulated brain area or network and the electrophysiological signal that we record. If target brain areas are functionally defined with prior fMRI scan, TMS could be used to link the fMRI activations with evoked potentials recorded. However, conducting such experiments presents significant technical challenges given the high amplitude artifacts introduced into the EEG signal by the magnetic pulse, and the difficulty to successfully target areas that were functionally defined by fMRI. Here we describe a methodology for combining these three common tools: TMS, EEG, and fMRI. We explain how to guide the stimulator&#39;s coil to the desired target area using anatomical or functional MRI data, how to record EEG during concurrent TMS, how to design an ERP study suitable for EEG-TMS combination and how to extract reliable ERP from the recorded data. We will provide representative results from a previously published study, in which fMRI-guided TMS was used concurrently with EEG to show that the face-selective N1 and the body-selective N1 component of the ERP are associated with distinct neural networks in extrastriate cortex. This method allows us to combine the high spatial resolution of fMRI with the high temporal resolution of TMS and EEG and therefore obtain a comprehensive understanding of the neural basis of various cognitive processes.

A concurrent EEG-TMS investigation was used to reveal whether the ERP responses to faces and bodies recorded over the occipito-temporal scalp are dissociated. When visual stimuli are presented, a prominent N1 component is recorded at posterior-lateral electrode sites. In particular, the N1 component is typically larger for faces and bodies than to other stimulus categories8,33. By assessing the effect of stimulation on face and body-selective brain areas defined with fMRI on their respective face and body N1 c...

Watch this Scientific Journal Video about Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation at JoVE.com

Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

This paper describes a method for collecting and analyzing electroencephalography (EEG) data during concurrent transcranial magnetic stimulation (TMS) guided by activations revealed with functional magnetic resonance imaging (fMRI). A method for TMS artifact removal and extraction of event related potentials is described as well as considerations in paradigm design and experimental setup.

Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological ...

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Neuroscience

13.7K Views.  Tel-Aviv University. This paper describes a method for collecting and analyzing electroencephalography (EEG) data during concurrent transcranial magnetic stimulation (TMS) guided by activations revealed with functional magnetic resonance imaging (fMRI). A method for TMS artifact removal and extraction of event related potentials is described as well as considerations in paradigm design and experimental setup.

Video: Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

Combining Transcranial Magnetic Stimulation and fMRI to Examine the Default Mode Network

The default mode network is a group of brain regions that are active when an individual is not focused on the outside world and the brain is at "wakeful rest."1,2,3 It is thought the default mode network corresponds to self-referential or "internal mentation".2,3
It has been hypothesized that, in humans, activity within the default mode network is correlated with certain pathologies (for instance, hyper-activation has been linked to schizophrenia 4,5,6 and autism spectrum disorders 7 whilst hypo-activation of the network has been linked to Alzheimer's and other neurodegenerative diseases 8). As such, noninvasive modulation of this network may represent a potential therapeutic intervention for a number of neurological and psychiatric pathologies linked to abnormal network activation. One possible tool to effect this modulation is Transcranial Magnetic Stimulation: a non-invasive neurostimulatory and neuromodulatory technique that can transiently or lastingly modulate cortical excitability (either increasing or decreasing it) via the application of localized magnetic field pulses.9
In order to explore the default mode network's propensity towards and tolerance of modulation, we will be combining TMS (to the left inferior parietal lobe) with functional magnetic resonance imaging (fMRI). Through this article, we will examine the protocol and considerations necessary to successfully combine these two neuroscientific tools.

In this article, we examine the methodology and considerations relevant to the combination of TMS and fMRI to examine the effects of brain stimulation on the default network.

The default mode network is a group of brain regions that are active when an individual is not focused on the outside world and the brain is at "wakeful ...

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

When considering human neuroimaging data, an appreciation of signal variability represents a fundamental innovation in the way we think about brain signal. Typically, researchers represent the brain's response as the mean across repeated experimental trials and disregard signal fluctuations over time as "noise". However, it is becoming clear that brain signal variability conveys meaningful functional information about neural network dynamics. This article describes the novel method of multiscale entropy (MSE) for quantifying brain signal variability. MSE may be particularly informative of neural network dynamics because it shows timescale dependence and sensitivity to linear and nonlinear dynamics in the data.

Neuroimaging researchers typically consider the brain's response as the mean activity across repeated experimental trials and disregard signal variability over time as "noise". However, it is becoming clear that there is signal in that noise. This article describes the novel method of multiscale entropy for quantifying brain signal variability in the time domain.

When considering human neuroimaging data, an appreciation of signal variability represents a fundamental innovation in the way we think about brain ...

Simultaneous Recording of Electroretinography and Visual Evoked Potentials in Anesthetized Rats

The electroretinogram (ERG) and visual evoked potential (VEP) are commonly used to assess the integrity of the visual pathway. The ERG measures the electrical responses of the retina to light stimulation, while the VEP measures the corresponding functional integrity of the visual pathways from the retina to the primary visual cortex following the same light event. The ERG waveform can be broken down into components that reflect responses from different retinal neuronal and glial cell classes. The early components of the VEP waveform represent the integrity of the optic nerve and higher cortical centers. These recordings can be conducted in isolation or together, depending on the application. The methodology described in this paper allows simultaneous assessment of retinal and cortical visual evoked electrophysiology from both eyes and both hemispheres. This is a useful way to more comprehensively assess retinal function and the upstream effects that changes in retinal function can have on visual evoked cortical function.

This protocol describes simultaneous measurement of electroretinogram and visual evoked potentials in anesthetized rats.

The electroretinogram (ERG) and visual evoked potential (VEP) are commonly used to assess the integrity of the visual pathway. The ERG measures the ...

Effects of Transcranial Alternating Current Stimulation on the Primary Motor Cortex by Online Combined Approach with Transcranial Magnetic Stimulation

Transcranial Alternating Current Stimulation (tACS) is a neuromodulatory technique able to act through sinusoidal electrical waveforms in a specific frequency and in turn modulate ongoing cortical oscillatory activity. This neurotool allows the establishment of a causal link between endogenous oscillatory activity and behavior. Most of the tACS studies have shown online effects of tACS. However, little is known about the underlying action mechanisms of this technique because of the AC-induced artifacts on Electroencephalography (EEG) signals. Here we show a unique approach to investigate online physiological frequency-specific effects of tACS of the primary motor cortex (M1) by using single pulse Transcranial Magnetic Stimulation (TMS) to probe cortical excitability changes. In our setup, the TMS coil is placed over the tACS electrode while Motor Evoked Potentials (MEPs) are collected to test the effects of the ongoing M1-tACS. So far, this approach has mainly been used to study the visual and motor systems. However, the current tACS-TMS setup can pave the way for future investigations of cognitive functions. Therefore, we provide a step-by-step manual and video guidelines for the procedure.

Transcranial Alternating Current Stimulation (tACS) allows the modulation of cortical excitability in a frequency-specific fashion. Here we show a unique approach which combines online tACS with single pulse Transcranial Magnetic Stimulation (TMS) in order to "probe" cortical excitability by means of Motor Evoked Potentials.

Transcranial Alternating Current Stimulation (tACS) is a neuromodulatory technique able to act through sinusoidal electrical waveforms in a specific ...

Visual Evoked Potential Recordings in Mice Using a Dry Non-invasive Multi-channel Scalp EEG Sensor

For scalp EEG research environments with laboratory mice, we designed a dry-type 16 channel EEG sensor which is non-invasive, deformable, and re-usable because of the plunger-spring-barrel structural facet and mechanical strengths resulting from metal materials. The whole process for acquiring the VEP responses in vivo from a mouse consists of four steps: (1) sensor assembly, (2) animal preparation, (3) VEP measurement, and (4) signal processing. This paper presents representative measurements of VEP responses from multiple mice with a submicro-voltage signal resolution and sub-hundred millisecond temporal resolution. Although the proposed method is safer and more convenient compared to other previously reported animal EEG acquiring methods, there are remaining issues including how to enhance the signal-to-noise ratio and how to apply this technique with freely moving animals. The proposed method utilizes easily available resources and shows a repetitive VEP response with a satisfactory signal quality. Therefore, this method could be utilized for longitudinal experimental studies and reliable translational research exploiting non-invasive paradigms.

We designed a dry-type 16 channel EEG sensor which is non-invasive, deformable, and re-usable. This paper describes the whole process from manufacturing the proposed EEG electrode to signal processing of visual evoked potential (VEP) signals measured on a mouse scalp using a dry non-invasive multi-channel EEG sensor.

For scalp EEG research environments with laboratory mice, we designed a dry-type 16 channel EEG sensor which is non-invasive, deformable, and re-usable ...

Event Related Potentials (ERPs) and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder (ADHD)

Neuropsychiatric diagnoses like ADHD are based on subjective methods like interviews, rating scales and observations. There is a need for more brain-based supplements. Stimulant medication is the most common treatment for ADHD. Clinically useful predictors of response have so far not been reported. The aim of this paper is to describe the EEG based methods we apply to extract potential biomarkers for brain dysfunction. Examples relate to biomarkers for pediatric ADHD, and prediction of medication response. The main emphasis is on Event Related Potentials (ERPs).
A nineteen channel EEG is recorded during a 3 min eyes-opened task, a 3 min eyes-closed task, and a 20 min cued visual GO/NOGO task (VCPT). ERPs are recorded during this task. The goal of the ERP protocol is to extract biomarkers of assumed brain dysfunctions that significantly differentiate between a patient group and healthy controls. The protocol includes recording during standard conditions and artifact correction. ERP waves can be used or transformed into latent components. The components of the patient group are compared with controls, empathizing components that, when compared, show relatively high effect sizes. Sub-groups of the patients are selected on the basis of the cluster analysis in the space of the components. Treatment procedure (such as medication, tDCS or neurofeedback protocol) can be applied and the changes in components related to treatment in the subgroups are observed, forming the basis for clinical recommendations.
The methods described were applied in a study of 87 pediatric ADHD patients. The index of medication response discriminated significantly between responders and non-responders with a large, and clinically meaningful effect size (d = 1.84). In an ongoing study comparing ADHD children with matched controls, several variables discriminate significantly between patients and controls. The global index will exceed d = .8. The EEG based methods described here could be clinically meaningful.

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

EEG-methods are applied for extracting biomarkers of brain dysfunctions. The focus is on multi-channel event-related potentials (ERPs) recorded in a cued GO/NOGO task. Non-brain artifacts are corrected and ERPs are compared with the normative data. Examples relate to biomarkers for ADHD diagnosis and prediction of medication response.

Neuropsychiatric diagnoses like ADHD are based on subjective methods like interviews, rating scales and observations. There is a need for more brain-based ...

Simultaneous Application of Transcranial Direct Current Stimulation during Virtual Reality Exposure

Transcranial direct current stimulation (tDCS) is a form of non-invasive brain stimulation that changes the likelihood of neuronal firing through modulation of neural resting membranes. Compared to other techniques, tDCS is relatively safe, cost-effective, and can be administered while individuals are engaged in controlled, specific cognitive processes. This latter point is important as tDCS may predominantly affect intrinsically active neural regions. In an effort to test tDCS as a potential treatment for psychiatric illness, the protocol described here outlines a novel procedure that allows the simultaneous application of tDCS during exposure to trauma-related cues using virtual reality (tDCS+VR) for veterans with posttraumatic stress disorder (NCT03372460). In this double-blind protocol, participants are assigned to either receive 2 mA tDCS, or sham stimulation, for 25 minutes while passively watching three 8-minute standardized virtual reality drives through Iraq or Afghanistan, with virtual reality events increasing in intensity during each drive. Participants undergo six sessions of tDCS+VR over the course of 2-3 weeks, and psychophysiology (skin conductance reactivity) is measured throughout each session. This allows testing for within and between session changes in hyperarousal to virtual reality events and adjunctive effects of tDCS. Stimulation is delivered through a built-in rechargeable battery-driven tDCS device using a 1 (anode) x 1 (cathode) unilateral electrode set-up. Each electrode is placed in a 3 x 3 cm (current density 2.22 A/m2) reusable sponge pocket saturated with 0.9% normal saline. Sponges with electrodes are attached to the participant&#8217;s skull using a rubber headband with the electrodes placed such that they target regions within the ventromedial prefrontal cortex. The virtual reality headset is placed over the tDCS montage in such a way as to avoid electrode interference.

This manuscript outlines a novel protocol to allow the simultaneous application of transcranial direct current stimulation during exposure to warzone trauma-related cues using virtual reality for veterans with posttraumatic stress disorder.

Transcranial direct current stimulation (tDCS) is a form of non-invasive brain stimulation that changes the likelihood of neuronal firing through ...

Objectively Assessing Sports Concussion Utilizing Visual Evoked Potentials

A portable system capable of measuring steady-state visual-evoked potentials (SSVEP) was developed to provide an objective, quantifiable method of electroencephalogram (EEG) testing following a traumatic event. In this study, the portable system was used on 65 healthy rugby players throughout a season to determine whether SSVEP are a reliable electrophysiological biomarker for concussion. Preceding the competition season, all players underwent a baseline SSVEP assessment. During the season, players were re-tested within 72 h of a match for either test-retest reliability or post-injury assessment. In the case of a medically diagnosed concussion, players were reassessed again once deemed recovered by a physician. The SSVEP system consisted of a smartphone housed in a VR-frame delivering a 15 Hz flicker stimulus, while a wireless EEG headset recorded occipital activity. Players were instructed to stare at the screen's fixation point while remaining seated and quiet. Electrodes were arranged according to the 10-20 EEG-positioning nomenclature, with O1-O2 being the recording channels while P1-P2 the references and bias, respectively. All EEG data was processed using a Butterworth bandpass filter, Fourier transformation, and normalization to convert data for frequency analysis. Players SSVEP responses were quantified into a signal-to-noise ratio (SNR), with 15 Hz being the desired signal, and summarized into respective study groups for comparison. Concussed players were seen to have a significantly lower SNR compared to their baseline; however, post-recovery, their SNR was not significantly different from the baseline. Test-retest indicated high device reliability for the portable system. An improved portable SSVEP system was also validated against an established EEG amplifier to ensure the investigative design is capable of obtaining research quality EEG measurements. This is the first study to identify differences in SSVEP responses in amateur athletes following a concussion and indicates the potential for SSVEP as an aid in concussion assessment and management.

A portable system capable of measuring steady-state visual-evoked potentials was developed and trialed on 65 amateur rugby players over 18 weeks to investigate SSVEP as a potential electrophysiological biomarker for concussion. Players' baselines were measured pre-season, with retesting for reliability, concussion, and recovery assessment being conducted within controlled time-periods, respectively.

A portable system capable of measuring steady-state visual-evoked potentials (SSVEP) was developed to provide an objective, quantifiable method of ...

﻿Participant Screening for Transcranial Magnetic Stimulation

Participant Screening for Transcranial Magnetic Stimulation  

To begin, screen the participant for any contraindications to transcranial magnetic stimulation, or TMS. Inform the participant about the study objectives and procedures. Review the risks outlined in the institution's ethics review board-approved consent document.Answer any questions about the potential risks and obtain written, informed consent before beginning any study procedures.

Enhancing TMS Efficacy with Sol Braiding Technique in Diverse Populations

The Sol Braiding Method for Handling Thick Hair During Transcranial Magnetic Stimulation: An Address for Potential Bias in Brain Stimulation

Transcranial Magnetic Stimulation (TMS) is a technique that is frequently utilized in neuroscience for both therapeutic and research purposes. TMS offers critical medical services like treating major depression and is vital in almost every research facility. Because TMS relies on scalp placement, hair is thought to affect efficacy because it varies the distance to the target site. Further, it is presumed that the hair textures and length that are predominantly seen in minoritized persons might pose significant challenges to collecting high-quality data. Here, we present preliminary data demonstrating that TMS may be influenced by hair, particularly in historically underrepresented minoritized groups.
The Sol braiding approach is introduced here as an easy-to-learn, quick-to-implement technique that reduces variability in TMS. Compared across nine participants, it was found that the Sol method significantly increased motor evoked potential (MEP) strength and consistency (p &#60; 0.05). By removing the physical hair barrier that impedes direct coil-to-scalp contact, the Sol approach enhances TMS delivery. The MEP peak amplitude and the MEP area under the curve (AUC) were shown to increase as a result. While preliminary, these data are an important step in addressing diversity in neuroscience. These procedures are explained for non-braiding experts.

Author Spotlight: Increasing TMS Accessibility Through Braiding Techniques for Diverse Hair Types

Hair type commonly seen in historically underrepresented minorities appears to interfere with transcranial magnetic stimulation (TMS). Here we describe a hair braiding method (The Sol Braiding Technique) that improves TMS.

Transcranial Magnetic Stimulation (TMS) is a technique that is frequently utilized in neuroscience for both therapeutic and research purposes. TMS offers ...